Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations250
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.7 KiB
Average record size in memory211.9 B

Variable types

Categorical2
Numeric10
DateTime1

Alerts

Bounce Rate is highly overall correlated with Source / MediumHigh correlation
Conversion Rate (%) is highly overall correlated with Quantity Sold and 2 other fieldsHigh correlation
Month of the year is highly overall correlated with YearHigh correlation
New Users is highly overall correlated with Pageviews and 5 other fieldsHigh correlation
Pageviews is highly overall correlated with New Users and 5 other fieldsHigh correlation
Quantity Sold is highly overall correlated with Conversion Rate (%) and 6 other fieldsHigh correlation
Revenue is highly overall correlated with Conversion Rate (%) and 6 other fieldsHigh correlation
Sessions is highly overall correlated with New Users and 5 other fieldsHigh correlation
Source / Medium is highly overall correlated with Bounce RateHigh correlation
Transactions is highly overall correlated with Conversion Rate (%) and 6 other fieldsHigh correlation
Users is highly overall correlated with New Users and 5 other fieldsHigh correlation
Year is highly overall correlated with Month of the yearHigh correlation
Bounce Rate has 3 (1.2%) zeros Zeros
Conversion Rate (%) has 46 (18.4%) zeros Zeros
Transactions has 46 (18.4%) zeros Zeros
Revenue has 46 (18.4%) zeros Zeros
Quantity Sold has 46 (18.4%) zeros Zeros

Reproduction

Analysis started2025-06-21 19:27:08.015718
Analysis finished2025-06-21 19:27:11.389252
Duration3.37 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Source / Medium
Categorical

High correlation 

Distinct38
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size14.4 KiB
A
 
12
K
 
12
C
 
12
Z
 
12
B
 
12
Other values (33)
190 

Length

Max length18
Median length1
Mean length1.392
Min length1

Characters and Unicode

Total characters348
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)2.8%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A 12
 
4.8%
K 12
 
4.8%
C 12
 
4.8%
Z 12
 
4.8%
B 12
 
4.8%
F 12
 
4.8%
M 12
 
4.8%
S 11
 
4.4%
P 11
 
4.4%
U 11
 
4.4%
Other values (28) 133
53.2%

Length

2025-06-21T12:27:11.412943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a 12
 
4.8%
b 12
 
4.8%
m 12
 
4.8%
f 12
 
4.8%
k 12
 
4.8%
z 12
 
4.8%
c 12
 
4.8%
s 11
 
4.4%
p 11
 
4.4%
u 11
 
4.4%
Other values (30) 135
53.6%

Most occurring characters

ValueCountFrequency (%)
A 30
 
8.6%
F 28
 
8.0%
E 23
 
6.6%
K 23
 
6.6%
C 22
 
6.3%
l 22
 
6.3%
M 21
 
6.0%
B 18
 
5.2%
. 18
 
5.2%
I 15
 
4.3%
Other values (27) 128
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 348
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 30
 
8.6%
F 28
 
8.0%
E 23
 
6.6%
K 23
 
6.6%
C 22
 
6.3%
l 22
 
6.3%
M 21
 
6.0%
B 18
 
5.2%
. 18
 
5.2%
I 15
 
4.3%
Other values (27) 128
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 348
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 30
 
8.6%
F 28
 
8.0%
E 23
 
6.6%
K 23
 
6.6%
C 22
 
6.3%
l 22
 
6.3%
M 21
 
6.0%
B 18
 
5.2%
. 18
 
5.2%
I 15
 
4.3%
Other values (27) 128
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 348
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 30
 
8.6%
F 28
 
8.0%
E 23
 
6.6%
K 23
 
6.6%
C 22
 
6.3%
l 22
 
6.3%
M 21
 
6.0%
B 18
 
5.2%
. 18
 
5.2%
I 15
 
4.3%
Other values (27) 128
36.8%

Year
Categorical

High correlation 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size15.0 KiB
2020
161 
2019
89 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1000
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2020
3rd row2019
4th row2019
5th row2020

Common Values

ValueCountFrequency (%)
2020 161
64.4%
2019 89
35.6%

Length

2025-06-21T12:27:11.443525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-21T12:27:11.466923image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2020 161
64.4%
2019 89
35.6%

Most occurring characters

ValueCountFrequency (%)
2 411
41.1%
0 411
41.1%
1 89
 
8.9%
9 89
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 411
41.1%
0 411
41.1%
1 89
 
8.9%
9 89
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 411
41.1%
0 411
41.1%
1 89
 
8.9%
9 89
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 411
41.1%
0 411
41.1%
1 89
 
8.9%
9 89
 
8.9%

Month of the year
Real number (ℝ)

High correlation 

Distinct12
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.54
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.489811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5079371
Coefficient of variation (CV)0.53638182
Kurtosis-1.2563645
Mean6.54
Median Absolute Deviation (MAD)3
Skewness0.0003556329
Sum1635
Variance12.305622
MonotonicityNot monotonic
2025-06-21T12:27:11.518724image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 29
11.6%
10 23
9.2%
11 22
8.8%
9 22
8.8%
12 22
8.8%
1 22
8.8%
4 21
8.4%
2 20
8.0%
6 18
7.2%
3 18
7.2%
Other values (2) 33
13.2%
ValueCountFrequency (%)
1 22
8.8%
2 20
8.0%
3 18
7.2%
4 21
8.4%
5 29
11.6%
6 18
7.2%
7 16
6.4%
8 17
6.8%
9 22
8.8%
10 23
9.2%
ValueCountFrequency (%)
12 22
8.8%
11 22
8.8%
10 23
9.2%
9 22
8.8%
8 17
6.8%
7 16
6.4%
6 18
7.2%
5 29
11.6%
4 21
8.4%
3 18
7.2%

Users
Real number (ℝ)

High correlation 

Distinct238
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11295.556
Minimum41
Maximum126870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.554549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile102
Q1302.25
median850.5
Q37836
95-th percentile77110.45
Maximum126870
Range126829
Interquartile range (IQR)7533.75

Descriptive statistics

Standard deviation24516.361
Coefficient of variation (CV)2.1704431
Kurtosis7.660432
Mean11295.556
Median Absolute Deviation (MAD)731.5
Skewness2.8259631
Sum2823889
Variance6.0105197 × 108
MonotonicityNot monotonic
2025-06-21T12:27:11.599145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86 3
 
1.2%
119 2
 
0.8%
336 2
 
0.8%
102 2
 
0.8%
453 2
 
0.8%
475 2
 
0.8%
132 2
 
0.8%
123 2
 
0.8%
441 2
 
0.8%
618 2
 
0.8%
Other values (228) 229
91.6%
ValueCountFrequency (%)
41 1
 
0.4%
54 1
 
0.4%
73 1
 
0.4%
77 1
 
0.4%
81 1
 
0.4%
86 3
1.2%
87 1
 
0.4%
90 1
 
0.4%
94 1
 
0.4%
99 1
 
0.4%
ValueCountFrequency (%)
126870 1
0.4%
123361 1
0.4%
120625 1
0.4%
106551 1
0.4%
102123 1
0.4%
91043 1
0.4%
88579 1
0.4%
84343 1
0.4%
83031 1
0.4%
82671 1
0.4%

New Users
Real number (ℝ)

High correlation 

Distinct223
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8743.856
Minimum1
Maximum104308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.640427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.45
Q1144.25
median482.5
Q33687.75
95-th percentile63513.95
Maximum104308
Range104307
Interquartile range (IQR)3543.5

Descriptive statistics

Standard deviation20584.145
Coefficient of variation (CV)2.3541267
Kurtosis7.8100959
Mean8743.856
Median Absolute Deviation (MAD)458.5
Skewness2.8959301
Sum2185964
Variance4.2370703 × 108
MonotonicityNot monotonic
2025-06-21T12:27:11.683814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83 3
 
1.2%
20 3
 
1.2%
1 3
 
1.2%
558 2
 
0.8%
16 2
 
0.8%
433 2
 
0.8%
103 2
 
0.8%
104 2
 
0.8%
15 2
 
0.8%
73 2
 
0.8%
Other values (213) 227
90.8%
ValueCountFrequency (%)
1 3
1.2%
2 1
 
0.4%
3 2
0.8%
4 2
0.8%
6 1
 
0.4%
11 2
0.8%
13 2
0.8%
14 1
 
0.4%
15 2
0.8%
16 2
0.8%
ValueCountFrequency (%)
104308 1
0.4%
104020 1
0.4%
98574 1
0.4%
88428 1
0.4%
82461 1
0.4%
81585 1
0.4%
75361 1
0.4%
73239 1
0.4%
72520 1
0.4%
70326 1
0.4%

Sessions
Real number (ℝ)

High correlation 

Distinct244
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16091.296
Minimum125
Maximum194667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.723813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum125
5-th percentile142.7
Q1395.25
median1138
Q310214.25
95-th percentile99685.9
Maximum194667
Range194542
Interquartile range (IQR)9819

Descriptive statistics

Standard deviation35614.956
Coefficient of variation (CV)2.2133056
Kurtosis9.7636004
Mean16091.296
Median Absolute Deviation (MAD)967
Skewness3.0758425
Sum4022824
Variance1.2684251 × 109
MonotonicityDecreasing
2025-06-21T12:27:11.768601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
137 2
 
0.8%
481 2
 
0.8%
191 2
 
0.8%
135 2
 
0.8%
169 2
 
0.8%
268 2
 
0.8%
604 1
 
0.4%
569 1
 
0.4%
573 1
 
0.4%
596 1
 
0.4%
Other values (234) 234
93.6%
ValueCountFrequency (%)
125 1
0.4%
127 1
0.4%
129 1
0.4%
130 1
0.4%
131 1
0.4%
132 1
0.4%
133 1
0.4%
135 2
0.8%
137 2
0.8%
139 1
0.4%
ValueCountFrequency (%)
194667 1
0.4%
194114 1
0.4%
181175 1
0.4%
170329 1
0.4%
163446 1
0.4%
142637 1
0.4%
133736 1
0.4%
125423 1
0.4%
125318 1
0.4%
110546 1
0.4%

Bounce Rate
Real number (ℝ)

High correlation  Zeros 

Distinct240
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.311
Minimum0
Maximum98.63
Zeros3
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.810971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.129
Q134.99
median52.76
Q361.79
95-th percentile83.052
Maximum98.63
Range98.63
Interquartile range (IQR)26.8

Descriptive statistics

Standard deviation20.234375
Coefficient of variation (CV)0.41034202
Kurtosis-0.35667679
Mean49.311
Median Absolute Deviation (MAD)11.885
Skewness-0.25733499
Sum12327.75
Variance409.42994
MonotonicityNot monotonic
2025-06-21T12:27:11.854697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
1.2%
33.33 2
 
0.8%
53.63 2
 
0.8%
63.12 2
 
0.8%
55.57 2
 
0.8%
61.56 2
 
0.8%
56.15 2
 
0.8%
75.92 2
 
0.8%
55.92 2
 
0.8%
51.06 1
 
0.4%
Other values (230) 230
92.0%
ValueCountFrequency (%)
0 3
1.2%
5.55 1
 
0.4%
6.98 1
 
0.4%
10.51 1
 
0.4%
11.46 1
 
0.4%
11.92 1
 
0.4%
11.94 1
 
0.4%
12.37 1
 
0.4%
12.58 1
 
0.4%
12.67 1
 
0.4%
ValueCountFrequency (%)
98.63 1
0.4%
91.75 1
0.4%
87.86 1
0.4%
87.71 1
0.4%
87.07 1
0.4%
86.53 1
0.4%
86.25 1
0.4%
86.13 1
0.4%
85.94 1
0.4%
85.68 1
0.4%

Pageviews
Real number (ℝ)

High correlation 

Distinct246
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44112.144
Minimum237
Maximum559509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:11.895214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum237
5-th percentile470.85
Q11382
median4440.5
Q331878.25
95-th percentile290432.4
Maximum559509
Range559272
Interquartile range (IQR)30496.25

Descriptive statistics

Standard deviation93892.52
Coefficient of variation (CV)2.128496
Kurtosis8.4078908
Mean44112.144
Median Absolute Deviation (MAD)3679
Skewness2.8908723
Sum11028036
Variance8.8158053 × 109
MonotonicityNot monotonic
2025-06-21T12:27:11.984217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1188 2
 
0.8%
1234 2
 
0.8%
1581 2
 
0.8%
3616 2
 
0.8%
2657 1
 
0.4%
2209 1
 
0.4%
3109 1
 
0.4%
5096 1
 
0.4%
1436 1
 
0.4%
3164 1
 
0.4%
Other values (236) 236
94.4%
ValueCountFrequency (%)
237 1
0.4%
241 1
0.4%
275 1
0.4%
279 1
0.4%
287 1
0.4%
297 1
0.4%
324 1
0.4%
335 1
0.4%
396 1
0.4%
397 1
0.4%
ValueCountFrequency (%)
559509 1
0.4%
455159 1
0.4%
425410 1
0.4%
373356 1
0.4%
370798 1
0.4%
368907 1
0.4%
368803 1
0.4%
342257 1
0.4%
333480 1
0.4%
328822 1
0.4%
Distinct163
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2025-06-21 00:00:02
Maximum2025-06-21 00:06:49
Invalid dates0
Invalid dates (%)0.0%
2025-06-21T12:27:12.026964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:12.075954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Conversion Rate (%)
Real number (ℝ)

High correlation  Zeros 

Distinct128
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1505622
Minimum0
Maximum42.08
Zeros46
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:12.121583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.14
median0.42
Q30.7875
95-th percentile26.384
Maximum42.08
Range42.08
Interquartile range (IQR)0.6475

Descriptive statistics

Standard deviation8.1223409
Coefficient of variation (CV)2.5780608
Kurtosis9.0153665
Mean3.1505622
Median Absolute Deviation (MAD)0.31
Skewness3.1455588
Sum787.64056
Variance65.972421
MonotonicityNot monotonic
2025-06-21T12:27:12.163797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
18.4%
0.25 6
 
2.4%
0.23 6
 
2.4%
0.2 5
 
2.0%
0.42 4
 
1.6%
0.14 4
 
1.6%
0.26 4
 
1.6%
0.34 4
 
1.6%
0.11 4
 
1.6%
0.39 4
 
1.6%
Other values (118) 163
65.2%
ValueCountFrequency (%)
0 46
18.4%
0.03 1
 
0.4%
0.05 1
 
0.4%
0.07 1
 
0.4%
0.08 1
 
0.4%
0.09 2
 
0.8%
0.1 1
 
0.4%
0.11 4
 
1.6%
0.12 4
 
1.6%
0.13 1
 
0.4%
ValueCountFrequency (%)
42.08 1
0.4%
40.05 1
0.4%
38.61 1
0.4%
36.18 1
0.4%
33.22 1
0.4%
31.76 1
0.4%
31.75 1
0.4%
31.38 1
0.4%
31.02 1
0.4%
26.72 1
0.4%

Transactions
Real number (ℝ)

High correlation  Zeros 

Distinct104
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.052
Minimum0
Maximum1347
Zeros46
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:12.205021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median7.5
Q382.5
95-th percentile436.35
Maximum1347
Range1347
Interquartile range (IQR)81.25

Descriptive statistics

Standard deviation177.89185
Coefficient of variation (CV)2.0915658
Kurtosis16.796627
Mean85.052
Median Absolute Deviation (MAD)7.5
Skewness3.6230245
Sum21263
Variance31645.511
MonotonicityNot monotonic
2025-06-21T12:27:12.249898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
18.4%
1 17
 
6.8%
2 17
 
6.8%
4 15
 
6.0%
5 10
 
4.0%
3 9
 
3.6%
10 6
 
2.4%
7 6
 
2.4%
6 5
 
2.0%
8 4
 
1.6%
Other values (94) 115
46.0%
ValueCountFrequency (%)
0 46
18.4%
1 17
 
6.8%
2 17
 
6.8%
3 9
 
3.6%
4 15
 
6.0%
5 10
 
4.0%
6 5
 
2.0%
7 6
 
2.4%
8 4
 
1.6%
9 2
 
0.8%
ValueCountFrequency (%)
1347 1
0.4%
1138 1
0.4%
783 1
0.4%
730 1
0.4%
728 1
0.4%
657 1
0.4%
622 1
0.4%
601 1
0.4%
566 1
0.4%
531 1
0.4%

Revenue
Real number (ℝ)

High correlation  Zeros 

Distinct202
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14772.776
Minimum0
Maximum203552
Zeros46
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:12.292187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1218.75
median1373.5
Q314714.25
95-th percentile75754.2
Maximum203552
Range203552
Interquartile range (IQR)14495.5

Descriptive statistics

Standard deviation29755.532
Coefficient of variation (CV)2.014214
Kurtosis11.550246
Mean14772.776
Median Absolute Deviation (MAD)1373.5
Skewness3.1196753
Sum3693194
Variance8.8539169 × 108
MonotonicityNot monotonic
2025-06-21T12:27:12.337152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
18.4%
623 2
 
0.8%
644 2
 
0.8%
81 2
 
0.8%
63057 1
 
0.4%
66600 1
 
0.4%
38728 1
 
0.4%
880 1
 
0.4%
897 1
 
0.4%
773 1
 
0.4%
Other values (192) 192
76.8%
ValueCountFrequency (%)
0 46
18.4%
42 1
 
0.4%
47 1
 
0.4%
55 1
 
0.4%
70 1
 
0.4%
77 1
 
0.4%
80 1
 
0.4%
81 2
 
0.8%
97 1
 
0.4%
103 1
 
0.4%
ValueCountFrequency (%)
203552 1
0.4%
167113 1
0.4%
130744 1
0.4%
128552 1
0.4%
126137 1
0.4%
112265 1
0.4%
103253 1
0.4%
103001 1
0.4%
98161 1
0.4%
96195 1
0.4%

Quantity Sold
Real number (ℝ)

High correlation  Zeros 

Distinct123
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150.104
Minimum0
Maximum2402
Zeros46
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2025-06-21T12:27:12.380529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median14
Q3127.5
95-th percentile740.65
Maximum2402
Range2402
Interquartile range (IQR)125.5

Descriptive statistics

Standard deviation328.20991
Coefficient of variation (CV)2.1865501
Kurtosis17.611439
Mean150.104
Median Absolute Deviation (MAD)14
Skewness3.8103276
Sum37526
Variance107721.75
MonotonicityNot monotonic
2025-06-21T12:27:12.423121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
18.4%
1 14
 
5.6%
5 13
 
5.2%
2 10
 
4.0%
4 6
 
2.4%
8 6
 
2.4%
6 6
 
2.4%
12 4
 
1.6%
3 4
 
1.6%
22 4
 
1.6%
Other values (113) 137
54.8%
ValueCountFrequency (%)
0 46
18.4%
1 14
 
5.6%
2 10
 
4.0%
3 4
 
1.6%
4 6
 
2.4%
5 13
 
5.2%
6 6
 
2.4%
7 3
 
1.2%
8 6
 
2.4%
9 3
 
1.2%
ValueCountFrequency (%)
2402 1
0.4%
1987 1
0.4%
1927 1
0.4%
1504 1
0.4%
1430 1
0.4%
1360 1
0.4%
1150 1
0.4%
981 1
0.4%
843 1
0.4%
829 1
0.4%

Interactions

2025-06-21T12:27:10.968701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:08.151828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-21T12:27:09.124135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.427462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.744525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:10.025033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:10.295227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-06-21T12:27:10.907608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:11.218318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:08.493377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:08.776381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.097533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.398119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.717612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:09.998467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:10.266538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:10.637372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T12:27:10.938637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-21T12:27:12.457930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Bounce RateConversion Rate (%)Month of the yearNew UsersPageviewsQuantity SoldRevenueSessionsSource / MediumTransactionsUsersYear
Bounce Rate1.000-0.461-0.1740.2880.243-0.069-0.0790.3850.511-0.0630.3880.225
Conversion Rate (%)-0.4611.000-0.170-0.0660.0030.6000.601-0.0720.4280.591-0.1060.000
Month of the year-0.174-0.1701.0000.0320.067-0.063-0.0390.0470.000-0.0570.0390.984
New Users0.288-0.0660.0321.0000.8700.5420.5390.8740.2290.5600.9180.000
Pageviews0.2430.0030.0670.8701.0000.6550.6420.9650.2070.6680.9650.000
Quantity Sold-0.0690.600-0.0630.5420.6551.0000.9870.6350.1260.9910.5910.062
Revenue-0.0790.601-0.0390.5390.6420.9871.0000.6220.2430.9920.5790.000
Sessions0.385-0.0720.0470.8740.9650.6350.6221.0000.2490.6490.9870.000
Source / Medium0.5110.4280.0000.2290.2070.1260.2430.2491.0000.2320.2440.181
Transactions-0.0630.591-0.0570.5600.6680.9910.9920.6490.2321.0000.6070.000
Users0.388-0.1060.0390.9180.9650.5910.5790.9870.2440.6071.0000.000
Year0.2250.0000.9840.0000.0000.0620.0000.0000.1810.0000.0001.000

Missing values

2025-06-21T12:27:11.265206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-21T12:27:11.355165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Source / MediumYearMonth of the yearUsersNew UsersSessionsBounce RatePageviewsAvg. Session DurationConversion Rate (%)TransactionsRevenueQuantity Sold
0A20191112687010402019466771.5945515900:01:110.2039483244482
1A202051206259857419411464.5655950900:01:320.6913472035522402
2A20191012336110430818117541.9136890700:01:050.2647794282599
3A201991065518842817032975.9236880300:01:010.1831154971415
4A202061021238246116344667.1042541000:01:200.7011381671131987
5A201912910437032614263767.0637079800:01:200.34486103001607
6A20201830316410313373669.4637335600:01:230.45601128552777
7A20207843437323912542371.1629226300:01:120.58730981611360
8A20202826266814512531870.0632882200:01:240.52657126137981
9A20203738446155711054672.1926618700:01:150.4853196195843
Source / MediumYearMonth of the yearUsersNew UsersSessionsBounce RatePageviewsAvg. Session DurationConversion Rate (%)TransactionsRevenueQuantity Sold
240U2019990831370.0046500:03:4318.9826590842
241KK2020511911213526.6754600:03:400.00000
242JJ20201947113528.89122600:06:492.96421115
243EE2019977313330.8397000:05:356.028150614
244JJ202051099113233.3384000:04:390.7611301
245AA202051119713161.0732400:01:260.00000
246K202021128113068.4629700:01:200.00000
247JJ2019121179012929.46100000:05:360.781811
248K202031117012762.2039700:01:270.791771
249euromessage / push2020599112560.8039600:01:440.00000